Newsroom

Graph Learning

  • FDS Colloquium: Jun’ichi Takeuchi (Kyushu), “Fisher information and Neural Tangent Kernels”

    Abstract: We argue relation between neural tangent kernels (NTK) and Fisher information matrices of neural networks. For the Fisher information matrices of two layer ReLU neural networks with random hidden weights, we demonstrated their approximate spectral decomposition, whose eigenvalue distribution highly concentrates (Takeishi et al. 2023). In particular, the sum of the top 3 eigenvalues…

  • FDS Colloquium: Quanquan C. Liu, “Massive Graph Algorithms from Theory to Practice and Back”

    “Massive Graph Algorithms from Theory to Practice and Back” Abstract: In the face of massive graph data, there is increased interest in developing novel algorithmic foundations for practical graph algorithms that are scalable, efficient, and private. Algorithm designers face many challenges when creating algorithms for real-world deployment. First, modern datasets often reach sizes of hundreds…